Do search terms matter for online consumers? The interplay between search engine query specification and topical organization

2007 ◽  
Vol 44 (1) ◽  
pp. 159-174 ◽  
Author(s):  
Nanda Kumar ◽  
Karl R. Lang
Keyword(s):  
Search Engine ◽  
Search Terms ◽  
Online Consumers

scholarly journals The yield and usefulness of PAIN+ and PubMed databases for accessing research evidence on pain management: a randomized crossover trial

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Vanitha Arumugam ◽  
Joy C. MacDermid ◽  
Dave Walton ◽  
Ruby Grewal
Keyword(s):  
Clinical Practice ◽  
Pain Management ◽  
Search Engine ◽  
Crossover Trial ◽  
Perceived Usefulness ◽  
Similar Process ◽  
Clinical Question ◽  
Current Clinical Practice ◽  
Search Terms ◽  
Randomized Crossover Trial

Abstract Introduction PAIN+ and PubMed are two electronic databases with two different mechanisms of evidence retrieval. PubMed is used to “Pull” evidence where clinicians can enter search terms to find answers while PAIN+ is a newly developed evidence repository where along with “Pull” service there is a “Push” service that alerts users about new research and the associated quality ratings, based on the individual preferences for content and altering criteria. Purpose The primary purpose of the study was to compare yield and usefulness of PubMed and PAIN+ in retrieving evidence to address clinical research questions on pain management. The secondary purpose of the study was to identify what search terms and methods were used by clinicians to target pain research. Study design Two-phase double blinded randomized crossover trial. Methods Clinicians (n = 76) who were exposed to PAIN+ for at least 1 year took part in this study. Participants were required to search for evidence 2 clinical question scenarios independently. The first clinical question was provided to all participants and thus, was multi-disciplinary. Participants were randomly assigned to search for evidence on their clinical question using either PAIN+ or PubMed through the electronic interface. Upon completion of the search with one search engine, they were crossed over to the other search engine. A similar process was done for a second scenario that was discipline-specific. The yield was calculated using number of retrieved articles presented to participants and usefulness was evaluated using a series of Likert scale questions embedded in the testing. Results Multidisciplinary scenario: Overall, the participants had an overall one-page yield of 715 articles for PAIN+ and 1135 articles for PubMed. The topmost article retrieved by PAIN+ was rated as more useful (p = 0.001). While, the topmost article retrieved by PubMed was rated as consistent with current clinical practice (p = 0.02). PubMed (48%) was preferred over PAIN+ (39%) to perform multidisciplinary search (p = 0.02). Discipline specific scenario: The participants had an overall one-page yield of 1046 articles for PAIN+ and 1398 articles for PubMed. The topmost article retrieved by PAIN+ was rated as more useful (p = 0.001) and consistent with current clinical practice (p = 0.02) than the articles retrieved by PubMed. PAIN+ (52%) was preferred over PubMed (29%) to perform discipline specific search. Conclusion Clinicians from different disciplines find both PAIN+ and PubMed useful for retrieving research studies to address clinical questions about pain management. Greater preferences and perceived usefulness of the top 3 retrieved papers was observed for PAIN+, but other dimensions of usefulness did not consistently favor either search engine. Trial registration Registered with ClinicalTrials.gov Identifier: NCT01348802, Date: May 5, 2011.

Team Co-occurence in Internet Search Engine Queries: An Analysis of the Excite Data Set

2013 ◽  
Author(s):  
Dietmar Wolfram
Keyword(s):  
Search Engine ◽  
Internet Search ◽  
Data Set ◽  
Search Terms ◽  
Internet Search Engine ◽  
Term Pair ◽  
Empirical Regularities

Unique queries submitted to the Excite search engine were analyzed for empirical regularities in the co-occurrence of search terms. The distribution of frequency of term pair occurrences was fitted to three models used in informetric studies to determine whether the pattern of term usage followed a Zipfian distribution. Relatively poor fits were obtained for two of the models tested. . .

scholarly journals Family planning in Louisiana and Mississippi, 2014-2018: Using application programming interfaces to access Google data and gain insights into searches on birth control (Preprint)

2020 ◽  
Author(s):  
Ndola Prata ◽  
Karen Weidert ◽  
Anne Zepecki ◽  
Elina Yon ◽  
Elizabeth Pleasants ◽  
...  
Keyword(s):  
United States ◽  
Family Planning ◽  
Health Information ◽  
Search Engine ◽  
Birth Control ◽  
The United States ◽  
Health Trends ◽  
Search Terms ◽  
Search Volume ◽  
Birth Control Pills

BACKGROUND It is now common to search for health information online, yet not much is known about online searches related to birth control. A 2013 PEW Research Center survey found that 77% of online health seekers began their query at a search engine. The widespread use of online health information seeking also applies to women’s reproductive health. Despite online interest in birth control, not much is known about related interests and concerns reflected in the search terms in the United States. OBJECTIVE In this study, we identify the top search terms on Google related to birth control in Louisiana and Mississippi and compare those results to the broader United States, examining how the Google searches have evolved over time and identifying regional variation within states. METHODS We accessed search data on birth control from 2014- 2018 from two proprietary Google Application Program Interfaces (APIs), Google Trends and Google Health Trends. We selected Google as it is the most commonly used search engine. We focused our analysis on data from 2017 and comparisons with 2018 data were made as appropriate. To assess trends, we analyzed data from 2014 through 2018. To compare the relative search frequencies of the top queries across Louisiana, Mississippi and the United States, we used the Google Health Trends API. Relative search volume by designated marketing area (DMA) gave us the rankings of search volume for each birth control method in each DMA as compared to one another. RESULTS Results showed that when people search for birth control in Louisiana and the broader United States, they are searching for information on a diverse spectrum of methods. This differs from Mississippi, where the data indicate people were mainly searching for information related to birth control pills. Across all locations, searches for birth control pills were significantly higher than any other queries related to birth control in the United States, Louisiana and Mississippi and this trend remained constant from 2014-2018. Regional level analysis shows variations in search traffic for birth control across each state. CONCLUSIONS The Internet is a growing source of health information for many users, including information on birth control. Understanding popular Google search queries on birth control can inform in-person discussion initiated by family planning practitioners and inform birth control messaging. INTERNATIONAL REGISTERED REPORT RR2-10.2196/16543

Google Scholar's Filter Bubble

2017 ◽  
pp. 211-229
Author(s):  
Ke Yu ◽  
Nazeem Mustapha ◽  
Nadeem Oozeer
Keyword(s):  
Social Science ◽  
Search Engine ◽  
Google Scholar ◽  
Online Search ◽  
Search Behaviour ◽  
Search Results ◽  
Search Terms ◽  
Exploratory Experiment ◽  
Filter Bubble ◽  
Academic Search

This chapter investigates the allegation that popular online search engine Google applies algorithms to personalise search results therefore yielding different results for the exact same search terms. It specifically examines whether the same alleged filter bubble applies to Google's academic product: Google Scholar. It reports the results from an exploratory experiment of nine keywords carried out for this purpose, varying variables such as disciplines (Natural Science, Social Science and Humanities), geographic locations (north/south), and levels (senior/junior researchers). It also reports a short survey on academic search behaviour. The finding suggests that while Google Scholar, together with Google, has emerged as THE dominant search engine among the participants of this study, the alleged filter bubble is only mildly observable. The Jaccard similarity of search results for all nine keywords is strikingly high, with only one keyword that exhibits a localized bubble at 95% level. This chapter therefore concludes that the filter bubble phenomenon does not warrant concern.

The black crow of science and its impact: analyzing Sci-Hub use with Google Trends

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emad Behboudi ◽  
Amrollah Shamsi ◽  
Gema Bueno de la Fuente
Keyword(s):  
Search Engine ◽  
Ethics Education ◽  
Ethics Committees ◽  
Research Process ◽  
Research Literature ◽  
Google Trends ◽  
Time Range ◽  
Web Searches ◽  
Content Type ◽  
Search Terms

PurposeIn 2016, Bohannon published an article analyzing the download rate of the top ten countries using the illegal Sci-Hub website. Four years later, this study approaches the search behavior of these ten countries as they query about Sci-Hub in Google's search engine, the world's most widely used search engine. The authors also tracked the possible consequences of using Sci-Hub, such as plagiarism.Design/methodology/approachThe search terms “Sci-Hub”, “Plagiarism” and “Plagiarism Checker” were explored with Google Trends. The queries were performed globally and individually for the ten target countries, all categories and web searches. The time range was limited between 1/1/2016 (after the date of publication of Bohannon's work) and 29/03/2020. Data were extracted from Google Trends and the findings were mapped.FindingsSearching for the word Sci-Hub on Google has increased nearly eightfold worldwide in the last four years, with China, Ethiopia and Tunisia having the most searches. Sci-Hub's search trends increased for most of the T10C, with Brazil and Iran having the highest and lowest average searches, respectively.Originality/valueAccess to the research literature is required to the progress of research, but it should not be obtained illegally. Given the increasing incidence of these problems in countries at any level of development, it is important to pay attention to ethics education in research and establish ethics committees. A comprehensive review of the research process is required to reduce the urge to circumvent copyright laws and includes training and educating research stakeholders in copyright literacy. To address these goals, national and international seriousness and enthusiasm are essential.

scholarly journals Distinct Diurnal and Day of Week Online Search Patterns Related to Common Eye Conditions

2020 ◽  
Author(s):  
Michael S. Deiner ◽  
Stephen D. McLeod ◽  
Julie M. Schallhorn ◽  
James Chodosh ◽  
Daniel H. Hwang ◽  
...  
Keyword(s):  
Search Engine ◽  
Time Of Day ◽  
Online Search ◽  
Eye Care ◽  
Cyclic Patterns ◽  
Diurnal Patterns ◽  
Search Terms ◽  
Eye Health ◽  
Search Patterns ◽  
Search Data

AbstractImportanceStudies suggest diurnal patterns of some eye conditions. Leveraging new information sources such as online search data to learn more about such patterns could improve understanding of patient eye-related conditions and well-being and improve timing of clinical and remote eye care.ObjectiveTo investigate our hypothesis that the public is likely to consistently search about different eye conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to eye conditions such as conjunctivitis. We asked if search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other.DesignHourly search data for eye-related and control search terms for 2018 were analyzed and compared.SettingData from 10 USA states.ExposureInternet search.ParticipantsPopulations that searched Google’s search engine using our chosen study terms.Main Outcome MeasuresCyclical hourly and weekly online search patterns.ResultsDistinct diurnal (p<0.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented reported clinical patterns. Of the eye related terms, “conjunctivitis” and “pink eye” had the strongest diurnal cyclic patterns based on peak-to-trough ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. In contrast, “dry eyes” had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening to morning period and peaking in early morning.Conclusions and RelevanceThe frequency of online searches for various eye conditions can show cyclic patterns according to time of day or week. Further studies to understand the reasons for these variations may help supplement current clinical understanding of eye symptom presentation and improve the timeliness of patient messaging and care interventions.Key PointsQuestionDo online public search engine queries for different eye-health terms follow hourly or daily patterns and do the patterns differ from each other or reflect what is known clinically?FindingsUnique hourly and day of week eye health related search patterns appear diurnal and can reflect what has been observed clinically.MeaningOnline search data may reflect timing of eye conditions and could improve clinical understanding of eye-related symptom occurrence, including outside of clinics. Knowing precisely when patient’s eye condition interests increase holds promise -for example to optimize timing and availability of local or remote eye care resources.

scholarly journals Managing Institutional Bibliographies using the ADS API: A new workflow using Google Sheets

2018 ◽  
Vol 186 ◽  
pp. 12003
Author(s):  
James Damon ◽  
Edwin Henneken ◽  
Alberto Accomazzi
Keyword(s):  
Search Engine ◽  
Human Error ◽  
Technical Skills ◽  
False Positives ◽  
Iterative Approach ◽  
Web Interface ◽  
Significant Time ◽  
Search Terms ◽  
Pertinent Information ◽  
Manual Review

Curating institutional bibliographies with the ADS web interface is currently a manual process that scales with the number of search terms. Long author lists and institutions with multiple sub-organizations or name variations increase the workload. Review work is monotonous and can take significant time depending on the size of the institution and the frequency of reviews. Consequently, bibliographies generated in this way are costly and may suffer from human error. We propose a semi-automated workflow that uses an iterative approach to discovery with ADS’s new search engine and a recently developed Google Sheets add on. First, affiliation strings from a user created spreadsheet are searched with the ADS API and for each result the matched affiliation and the paired author are retrieved. Next, each author name string is searched and items where that author is paired with an empty affiliation field are retrieved. The results from both queries are then compiled into output sheets with pertinent information for manual review. Finally, the selected items can be added to an ADS library from the Google Sheets interface. The tool can also use previously rejected affiliation strings to flag false positives in subsequent queries. Curators do not need to have extensive technical skills in order to use the workflow and they can help improve the ADS by opting to share ORCIDs, author synonyms, and affiliation synonyms.

scholarly journals Detecting epidemiological relevance among adenoid hypertrophy, rhinosinusitis, and allergic rhinitis through Internet search

2021 ◽  
Author(s):  
Yingchao Yang ◽  
Xinyi Li ◽  
Qiang Ma ◽  
Zhihui Fu ◽  
Kaiming Su
Keyword(s):  
Allergic Rhinitis ◽  
Search Engine ◽  
Correlation Coefficients ◽  
Adenoid Hypertrophy ◽  
Internet Search ◽  
Search Terms ◽  
Search Volume ◽  
Internet Search Engine ◽  
Search Data

Abstract Purpose : This study aimed to verify that adenoid hypertrophy (AH) and rhinosinusitis share similar epidemiologic patterns and that AH and allergic rhinitis (AR) are not related. Methods: Internet search engine query data from January 2011 to December 2019 were retrieved from the Baidu index. Monthly search volume was obtained in China for the following search terms in Chinese: “adenoid hypertrophy,” “rhinosinusitis,” and “allergic rhinitis”; the data obtained were then presented as percentages. Pearson’s and Spearman’ s correlation coefficients were used to detect the correlation among the search volumes of AH, rhinosinusitis, and AR. We also collected search data from the first 5 months of 2020, when segregation was implemented in China due to the coronavirus disease 2019 epidemic. Then, we compared the search data to those obtained during the same period in 2019 to detect the effects of segregation on AH and AR to varying degrees. Results: Statistically significant differences were found between the search variations of AH and rhinosinusitis during 2011–2019 (R=0.643, P<0.05). However, search variations of AH and AR were negatively related (R=-0.239, P<0.05). The average monthly search volume of AH and rhinosinusitis correlated well (R=0.836, P<0.01), but no correlation was found between AH and AR. The search volume of AH and rhinosinusitis during the first 5 months in 2020 decreased, whereas that of AR increased during January–February. Conclusions: AH and rhinosinusitis are epidemiologically related, whereas AH and AR are not correlated with each other.

scholarly journals What did you see? A study to measure personalization in Google’s search engine

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Tobias D. Krafft ◽  
Michael Gamer ◽  
Katharina A. Zweig
Keyword(s):  
Search Engine ◽  
Similarity Measures ◽  
Similar Degree ◽  
Election Campaign ◽  
Proof Of Concept ◽  
Search Results ◽  
Search Terms ◽  
Filter Bubble ◽  
Filter Bubbles ◽  
Selective Access

AbstractIn this paper we present the results of the project “#Datenspende” where during the German election in 2017 more than 4000 people contributed their search results regarding keywords connected to the German election campaign.Analyzing the donated result lists we prove, that the room for personalization of the search results is very small. Thus the opportunity for the effect mentioned in Eli Pariser’s filter bubble theory to occur in this data is also very small, to a degree that it is negligible. We achieved these results by applying various similarity measures to the result lists that were donated. The first approach using the number of common results as a similarity measure showed that the space for personalization is less than two results out of ten on average when searching for persons and at most four regarding the search for parties. Application of other, more specific measures show that the space is indeed smaller, so that the presence of filter bubbles is not evident.Moreover this project is also a proof of concept, as it enables society to permanently monitor a search engine’s degree of personalization for any desired search terms. The general design can also be transferred to intermediaries, if appropriate APIs restrict selective access to contents relevant to the study in order to establish a similar degree of trustworthiness.

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